Model Calibrations
calibrate is a generic function used to produce calibrations
from various model fitting functions. The function invokes
particular ‘methods’ which depend on the ‘class’ of the first
argument.
calibrate(object, ...)
object |
An object for which a calibration is desired. |
... |
Additional arguments affecting the calibration produced.
Usually the most important argument in |
Given a regression model with explanatory variables X and
response Y,
calibration involves estimating X from Y using the
regression model.
It can be loosely thought of as the opposite of predict
(which takes an X and returns a Y of some sort.)
In general,
the central algorithm is maximum likelihood calibration.
In general, given a new response Y,
some function of the explanatory variables X are returned.
For example,
for constrained ordination models such as CQO and CAO models,
it is usually not possible to return X, so the latent
variables are returned instead (they are
linear combinations of the X).
See the specific calibrate methods functions to see
what they return.
This function was not called predictx because of the
inability of constrained ordination models to return X;
they can only return the latent variable values
(also known as site scores) instead.
T. W. Yee
ter Braak, C. J. F. and van Dam, H. (1989). Inferring pH from diatoms: a comparison of old and new calibration methods. Hydrobiologia, 178, 209–223.
## Not run:
hspider[, 1:6] <- scale(hspider[, 1:6]) # Stdzed environmental vars
set.seed(123)
pcao1 <- cao(cbind(Pardlugu, Pardmont, Pardnigr, Pardpull, Zoraspin) ~
WaterCon + BareSand + FallTwig + CoveMoss + CoveHerb + ReflLux,
family = poissonff, data = hspider, Rank = 1, Bestof = 3,
df1.nl = c(Zoraspin = 2, 1.9), Crow1positive = TRUE)
siteNos <- 1:2 # Calibrate these sites
cpcao1 <- calibrate(pcao1, trace = TRUE,
newdata = data.frame(depvar(pcao1)[siteNos, ],
model.matrix(pcao1)[siteNos, ]))
# Graphically compare the actual site scores with their calibrated values
persp(pcao1, main = "Site scores: solid=actual, dashed=calibrated",
label = TRUE, col = "blue", las = 1)
abline(v = latvar(pcao1)[siteNos], col = seq(siteNos)) # Actual scores
abline(v = cpcao1, lty = 2, col = seq(siteNos)) # Calibrated values
## End(Not run)Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.